Papers
Nested Chinese Restaurant Franchise Process: Applications to User Tracking and Document Modeling
Amr Ahmed, Liangjie Hong, Alexander Smola
Noisy and Missing Data Regression: Distribution-Oblivious Support Recovery
Yudong Chen, Constantine Caramanis
Noisy Sparse Subspace Clustering
Yu-Xiang Wang, Huan Xu
No more pesky learning rates
Tom Schaul, Sixin Zhang, Yann LeCun
Non-Linear Stationary Subspace Analysis with Application to Video Classification
Mahsa Baktashmotlagh, Mehrtash Harandi, Abbas Bigdeli et al.
Nonparametric Mixture of Gaussian Processes with Constraints
James Ross, Jennifer Dy
O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions
Lijun Zhang, Tianbao Yang, Rong Jin et al.
On A Nonlinear Generalization of Sparse Coding and Dictionary Learning
Jeffrey Ho, Yuchen Xie, Baba Vemuri
On autoencoder scoring
Hanna Kamyshanska, Roland Memisevic
On Compact Codes for Spatially Pooled Features
Yangqing Jia, Oriol Vinyals, Trevor Darrell
One-Bit Compressed Sensing: Provable Support and Vector Recovery
Sivakant Gopi, Praneeth Netrapalli, Prateek Jain et al.
One-Pass AUC Optimization
Wei Gao, Rong Jin, Shenghuo Zhu et al.
On learning parametric-output HMMs
Aryeh Kontorovich, Boaz Nadler, Roi Weiss
Online Feature Selection for Model-based Reinforcement Learning
Trung Nguyen, Zhuoru Li, Tomi Silander et al.
Online Kernel Learning with a Near Optimal Sparsity Bound
Lijun Zhang, Jinfeng Yi, Rong Jin et al.
Online Latent Dirichlet Allocation with Infinite Vocabulary
Ke Zhai, Jordan Boyd-Graber
Online Learning under Delayed Feedback
Pooria Joulani, Andras Gyorgy, Csaba Szepesvari
On the difficulty of training recurrent neural networks
Razvan Pascanu, Tomas Mikolov, Yoshua Bengio
On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions
Purushottam Kar, Bharath Sriperumbudur, Prateek Jain et al.
On the importance of initialization and momentum in deep learning
Ilya Sutskever, James Martens, George Dahl et al.
On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance
Aditya Menon, Harikrishna Narasimhan, Shivani Agarwal et al.
Optimal rates for stochastic convex optimization under Tsybakov noise condition
Aaditya Ramdas, Aarti Singh
Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning
Odalric-Ambrym Maillard, Phuong Nguyen, Ronald Ortner et al.
Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in Crowdsourcing
Xi Chen, Qihang Lin, Dengyong Zhou
Optimization with First-Order Surrogate Functions
Julien Mairal